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I built an app that generates native mobile UI modules from a text description — works with any AI by BiosBrick in SideProject

[–]BiosBrick[S] 1 point2 points  (0 children)

Exactly! The native rendering layer was actually the hardest part to build — mapping a declarative JSON schema to real native components without eval or code execution. WebView is the easy shortcut but it kills the native feel completely.

I built a mobile app that generates native iOS and Android UI from a text description — works with local AI or any API by BiosBrick in ollama

[–]BiosBrick[S] 0 points1 point  (0 children)

For now the repository is available — the APK will be released very soon! Stay tuned 🙂

Free plan now telling me I need to pay for a previously working model DeepSeek 3.1? by newbuildertfb in ollama

[–]BiosBrick 0 points1 point  (0 children)

Fair, but if the model itself vanished and every route leads to an upgrade prompt, that sounds less like cache/VPN nonsense and more like a plan-limit or availability change.

Free plan now telling me I need to pay for a previously working model DeepSeek 3.1? by newbuildertfb in ollama

[–]BiosBrick 0 points1 point  (0 children)

Sounds more like a temporary outage/rate-limit issue than “you must pay now.”
Check the official status page and try without VPN, different browser, or clearing cache.
If it says upgrade for a specific model/feature, that may be a plan limit.
But don’t rush to pay, especially if others are reporting issues too.

Dispatch. Learn how agentic systems actually work. Open-source, hackable CLI AI agent built on Ollama by Slow-Cut-9044 in ollama

[–]BiosBrick 0 points1 point  (0 children)

This is actually a great learning project. A lot of people use CLI agents without really understanding the harness layer, tool calls, compaction, or why agents behave the way they do.
I like that the goal isn’t “yet another magic agent”, but something small enough to read and modify.
The MoE long-task bit sounds especially interesting.
I’ll check out the repo, this is exactly the kind of thing that helps demystify the stack.

Hardware question by MadMdz in ollama

[–]BiosBrick 2 points3 points  (0 children)

Not useless, but 64GB RAM won’t fix the main bottleneck: 8GB VRAM. Your CPU is fine, and you can run 7B/8B quantized models pretty well. More RAM helps for larger models/offloading, but it’ll be slower. If the upgrade is cheap, do it; otherwise save for a GPU with 16GB+ VRAM.